predict.boosted_regression_forest function

Predict with a boosted regression forest.

Gets estimates of E[Y|X=x] using a trained regression forest.

## S3 method for class 'boosted_regression_forest'
predict(
  object,
  newdata = NULL,
  boost.predict.steps = NULL,
  num.threads = NULL,
  ...
)

Arguments

• object: The trained forest.
• newdata: Points at which predictions should be made. If NULL, makes out-of-bag predictions on the training set instead (i.e., provides predictions at Xi using only trees that did not use the i-th training example). Note that this matrix should have the number of columns as the training matrix, and that the columns must appear in the same order
• boost.predict.steps: Number of boosting iterations to use for prediction. If blank, uses the full number of steps for the object given
• num.threads: the number of threads used in prediction
• ...: Additional arguments (currently ignored).

Returns

A vector of predictions.

Examples

# Train a boosted regression forest.
n <- 50
p <- 10
X <- matrix(rnorm(n * p), n, p)
Y <- X[, 1] * rnorm(n)
r.boosted.forest <- boosted_regression_forest(X, Y)

# Predict using the forest.
X.test <- matrix(0, 101, p)
X.test[, 1] <- seq(-2, 2, length.out = 101)
r.pred <- predict(r.boosted.forest, X.test)

# Predict on out-of-bag training samples.
r.pred <- predict(r.boosted.forest)